Input image data
AI Models & Assistants / Knowledge library
GPT-5.2 Chat
GPT-5.2 model used in ChatGPT
Why learn GPT-5.2 Chat?
Offers the documented OpenAI model capabilities through hosted.
The problem it solves
Provides model inference for supported text / image inputs.
Where it came from
GPT-5.2 Chat: GPT-5.2 model used in ChatGPT Published aliases: gpt-5.2-chat-latest. Input: text, image. Output: text. Checked 2026-10-13. Model capabilities are distinct from tools available in a particular agent.
Build your understanding
Work through these exercises in order. Try the task before opening a reference.
- Explain what GPT-5.2 Chat does.
- Identify a use case for GPT-5.2 Chat.
- Describe a limitation of GPT-5.2 Chat.
- Name a compatible tool for GPT-5.2 Chat.
- Compare GPT-5.2 Chat against an alternative.
Documentation and sources
- Primary source / model card (developers.openai.com)
Catalog research notes
- See the AI Workbench for source dates, pricing evidence and configuration details.
Connect the ideas
Built on
Real World Example
Automated Architectural Compliance Review
Large-scale urban planning firms managing complex zoning regulations.
The business problem
Manual verification of architectural blueprints against thousands of pages of municipal zoning codes is error-prone and causes significant project delays.
How this topic solves it
Utilizing the GPT-5.2 Chat model via the Chat Completions API to ingest architectural site images and textual zoning requirements, performing cross-referenced compliance checks.
- Convert architectural site plans into image formats compatible with the model's input modalities.
- Structure municipal zoning regulations into a text-based knowledge base for context injection.
- Invoke the v1/chat/completions endpoint using the gpt-5.2-chat-latest model ID.
- Enable structured_outputs to ensure the model returns compliance findings in a machine-readable format.
- Implement streaming to provide immediate feedback to architects as the model analyzes specific building sections.
The flow shows how input data is processed by the model to generate compliance feedback.
Input text data
Processing engine
Structured output
- Architectural Plans → image_input → GPT-5.2 Chat
- Zoning Regulations → context_injection → GPT-5.2 Chat
- GPT-5.2 Chat → structured_outputs → Compliance Report
Implementation example
This snippet demonstrates calling the Chat Completions API with image and text inputs to trigger the compliance analysis defined in the scenario.
client.chat.completions.create(
model='gpt-5.2-chat-latest', # Specify the model snapshot
messages=[{'role': 'user', 'content': [{'type': 'image_url', 'image_url': {...}}, {'type': 'text', 'text': 'Check compliance'}]}],
response_format={'type': 'json_object'} # Enforce structured_outputs
)Expected business outcome
Architects receive rapid, preliminary compliance assessments, allowing for iterative design adjustments before formal submission.
Limitations and checks
The model may experience hallucinations regarding specific numerical setbacks; verify output by cross-referencing the model's cited zoning clauses against the source document.